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Large Language Models (LLMs) have come closest among all models to date to mastering human language, yet opinions about their linguistic and cognitive capabilities remain split. Here, we evaluate LLMs using a distinction between formal…

Computation and Language · Computer Science 2024-04-14 Kyle Mahowald , Anna A. Ivanova , Idan A. Blank , Nancy Kanwisher , Joshua B. Tenenbaum , Evelina Fedorenko

Choice constructs are an important part of the language of logic programming, yet the study of their semantics has been a challenging task. So far, only two-valued semantics have been studied, and the different proposals for such semantics…

Artificial Intelligence · Computer Science 2024-08-01 Jesse Heyninck

One of the central aspects of contextualised language models is that they should be able to distinguish the meaning of lexically ambiguous words by their contexts. In this paper we investigate the extent to which the contextualised…

Computation and Language · Computer Science 2021-09-30 Janosch Haber , Massimo Poesio

Knowledge facts are typically represented by relational triples, while we observe that some commonsense facts are represented by the triples whose forms are inconsistent with the expression of language. This inconsistency puts forward a…

Computation and Language · Computer Science 2021-06-01 Yi Zhang , Lei Li , Yunfang Wu , Qi Su , Xu Sun

Compositional generalization benchmarks for semantic parsing seek to assess whether models can accurately compute meanings for novel sentences, but operationalize this in terms of logical form (LF) prediction. This raises the concern that…

Computation and Language · Computer Science 2024-01-25 Zhengxuan Wu , Christopher D. Manning , Christopher Potts

A core problem in learning semantic parsers from denotations is picking out consistent logical forms--those that yield the correct denotation--from a combinatorially large space. To control the search space, previous work relied on…

Computation and Language · Computer Science 2016-11-17 Panupong Pasupat , Percy Liang

Analogical reasoning is at the core of human cognition, serving as an important foundation for a variety of intellectual activities. While prior work has shown that LLMs can represent task patterns and surface-level concepts, it remains…

Computation and Language · Computer Science 2025-11-26 Taewhoo Lee , Minju Song , Chanwoong Yoon , Jungwoo Park , Jaewoo Kang

Strong equivalence between knowledge bases ensures the possibility of replacing one with the other without affecting reasoning outcomes, in any given context. This makes it a crucial property in nonmonotonic formalisms. In particular, the…

Artificial Intelligence · Computer Science 2026-05-15 Giovanni Buraglio , Wolfgang Dvorak , Stefan Woltran

The words of a language reflect the structure of the human mind, allowing us to transmit thoughts between individuals. However, language can represent only a subset of our rich and detailed cognitive architecture. Here, we ask what kinds of…

Computation and Language · Computer Science 2018-03-07 Gabriel Grand , Idan Asher Blank , Francisco Pereira , Evelina Fedorenko

Reasoning with ontologies is one of the core fields of research in Description Logics. A variety of efficient reasoner with highly optimized algorithms have been developed to allow inference tasks on expressive ontology languages such as…

Artificial Intelligence · Computer Science 2015-10-01 Nourhène Alaya , Sadok Ben Yahia , Myriam Lamolle

Much work has been done on extending the well-founded semantics to general disjunctive logic programs and various approaches have been proposed. However, these semantics are different from each other and no consensus is reached about which…

Artificial Intelligence · Computer Science 2007-05-23 Kewen Wang , Lizhu Zhou

Logical fallacy uses invalid or faulty reasoning in the construction of a statement. Despite the prevalence and harmfulness of logical fallacies, detecting and classifying logical fallacies still remains a challenging task. We observe that…

Computation and Language · Computer Science 2024-10-17 Yuanyuan Lei , Ruihong Huang

Ontologies often require knowledge representation on multiple levels of abstraction, but description logics (DLs) are not well-equipped for supporting this. We propose an extension of DLs in which abstraction levels are first-class citizens…

Artificial Intelligence · Computer Science 2023-10-23 Carsten Lutz , Lukas Schulze

The paper relates two variants of semantic models for natural language, logical functional models and compositional distributional vector space models, by transferring the logic and reasoning from the logical to the distributional models.…

Logic in Computer Science · Computer Science 2014-12-31 Anne Preller

Semantic data and knowledge infrastructures must reconcile two fundamentally different forms of representation: natural language, in which most knowledge is created and communicated, and formal semantic models, which enable…

Computation and Language · Computer Science 2026-03-24 Lars Vogt

Large language models (LLMs) have achieved remarkable successes on various tasks. However, recent studies have found that there are still significant challenges to the logical reasoning abilities of LLMs, which can be categorized into the…

Artificial Intelligence · Computer Science 2025-07-22 Fengxiang Cheng , Haoxuan Li , Fenrong Liu , Robert van Rooij , Kun Zhang , Zhouchen Lin

Reasoning with quantifier expressions in natural language combines logical and arithmetical features, transcending strict divides between qualitative and quantitative. Our topic is this cooperation of styles as it occurs in common…

Logic · Mathematics 2025-07-08 Johan van Benthem , Thomas Icard

Normative reasoning is a type of reasoning that involves normative or deontic modality, such as obligation and permission. While large language models (LLMs) have demonstrated remarkable performance across various reasoning tasks, their…

Artificial Intelligence · Computer Science 2025-11-03 Kentaro Ozeki , Risako Ando , Takanobu Morishita , Hirohiko Abe , Koji Mineshima , Mitsuhiro Okada

This paper investigates the contingency of logic within the framework of possible world semantics. Possible world semantics captures the meaning of necessitation, i.e., a statement is necessarily true if it holds in all possible worlds.…

Although Large Language Models (LLMs) have demonstrated impressive formal reasoning abilities, they often break down when problems require complex proof planning. One promising approach for improving LLM reasoning abilities involves…

Artificial Intelligence · Computer Science 2026-01-27 Joseph Cotnareanu , Didier Chetelat , Yingxue Zhang , Mark Coates